1. Field of Invention
The present invention relates to a lossless image compression method, and more particularly to a lossless image compression method requiring little memory space.
2. Related Art
With advances in electronic and information technologies, the technology for processing and displaying images on computers or various electronic devices have developed to be more and more popular. The early electronic and information technologies can only store or process low-pixel digital images. However, people have more and more demands for high-quality images, so how to process and store high-quality images becomes a very popular focus. In order to obtain high-quality images, a lossless compression method is always used when performing image compression.
However, lossless high-quality images are required to store high pixels, which is a great challenge to the computing speed of a computer and the capacity of a storage medium. For example, in a lossless compression algorithm, the lossless static image compression standard (joint photographic experts group lossless, JPEG-LS) achieves a good compression ratio by using prediction and context modeling. The context modeling needs to at least buffer a whole row of pixels of the image, so as to perform prediction in various modes. As a result, a large amount of computation and storage space is required, and the cost of an encoder is increased. As for applications not requiring high compression ratio, the algorithmic complexity of the JPEG-LS is high, so that the load of the encoder is increased.
As the requirement for the image resolution of the user becomes higher and higher, the load in image compression is also increased. If a conventional lossless compression method is used, once the resolution of an image is enhanced, the encoder has to consume much time and a larger amount of storage space to process the image into a high-quality image. In other words, the conventional lossless compression method has the problems that the computational efficiency is low due to high computational complexity and large buffer space is required.
Therefore, how to design a lossless compression method that can balance the demands for high visual quality, low computational complexity, and small buffer space is a very important issue in the industry. A heretofore unaddressed need exists in the art to address the aforementioned deficiencies and inadequacies.